Early vascular aging determined by brachial-ankle pulse wave velocity and its impact on ischemic stroke outcome: a retrospective observational study

Vascular aging phenotype may be useful in predicting stroke prognosis. In the present study, the relationship between vascular aging phenotypes and outcomes after acute ischemic stroke was investigated. The study included consecutive patients with acute ischemic stroke who had brachial-ankle pulse wave velocity (baPWV) measured to assess vascular aging phenotype. The 2.5th and 97.5th percentile age-specific baPWVs were used as cutoffs to define supernormal vascular aging (SUPERNOVA) and early vascular aging (EVA), respectively, and the remainder was considered normal vascular aging (NVA). A total of 2738 patients were enrolled and followed for a median of 38.1 months. The mean age was 67.02 years and 1633 were male. EVA was 67, NVA was 2605, and SUPERNOVA was 66. Compared with NVA, multivariable logistic regression showed EVA was associated with poor functional outcome (modified Rankin Scale ≥ 3) at 3 months (odds ratio 2.083, 95% confidence interval 1.147‒3.783). Multivariable Cox regression showed EVA was associated with all-cause mortality (hazard ratio 2.320, 95% confidence interval 1.283‒4.197). EVA was associated with poor functional outcome and all-cause mortality after acute ischemic stroke, especially when diabetes or atrial fibrillation coexisted. These findings indicate the vascular aging phenotype, notably EVA, can aid in identifying high-risk stroke patients.

), all-cause mortality.The Kaplan-Meier curve analysis showed EVA was significantly associated with all-cause mortality (p = 0.005); however, SUPER-NOVA did not differ from NVA (Fig. 2).After adjusting for potential confounders (Supplementary Table 1), Cox regression analysis showed all-cause mortality was independently associated with EVA (hazard ratio [HR] 2.320, 95% CI 1.283-4.197,p = 0.005) but not with SUPERNOVA (HR 1.206, 95% CI 0.534-2.725,p = 0.652).In the model adjusted for atherosclerotic cardiovascular disease (ASCVD) risk factors, EVA remained an independent determinant of all-cause mortality.However, EVA and SUPERNOVA did not show an independent association with MACE and stroke recurrence (Table 3).

Subgroup analysis of poor outcomes
Multivariable logistic or Cox regression was utilized for subgroup analysis.In all strata, the effect of EVA tended to be associated with poor functional outcome and frequent all-cause mortality.However, a significant interaction was observed in patients with diabetes or atrial fibrillation.The presence of EVA was significantly associated with poor functional outcome in patients with diabetes (OR 3.798, 95% CI 1.736-8.310,p = 0.001) but not in subjects without (p-value for interaction = 0.023; Fig. 3A).In addition, EVA was significantly associated with allcause mortality in patients with atrial fibrillation (OR 5.755, 95% CI 2.822-11.735,p < 0.001) but not in subjects without (p-value for interaction = 0. 021; Fig. 3B).

Discussion
In this study, the presence of EVA was independently associated with poor functional outcome at 3 months and all-cause mortality after acute ischemic stroke.The unfavorable effect of EVA was more noticeable on functional outcome in patients with diabetes and on mortality in those with atrial fibrillation.In contrast, the prognosis of SUPERNOVA was similar to NVA in patients with acute ischemic stroke.The hallmark of vascular aging is arterial stiffness, which can be readily assessed by measuring baPWV.This measurement serves as a valuable tool to evaluate the present state of arterial health influenced by age, risk factors, and natural susceptibility 9 .In addition, baPWV can be used to monitor the response of arterial stiffness to therapy or its progression 10,11 .Moreover, the baPWV has become a standard for characterizing vascular aging because arterial stiffness captures the total damage experienced by the arterial wall and provides a more holistic perspective than traditional metrics such as blood pressure or lipid levels 1,12,13 .
In the present study, vascular aging categorized based on arterial stiffness was associated with unfavorable outcomes after acute ischemic stroke.The concept of vascular aging can be used to express cardiovascular risk based on estimated biological age and for prognosticating its occurrence in the general population 4,5 .Vascular aging can vary in presentation, independent of risk factors, due to imbalances in the protective genetic/molecular pathways 3 .Intrinsic vulnerability to vascular aging, such as EVA, may exacerbate arterial stiffness and future vascular events.Conversely, resistance to vascular aging, such as SUPERNOVA, may increase resilience to vascular disease 1 .Therefore, vascular aging phenotyping may provide additional information to predict stroke prognosis.
The EVA phenotype is characterized by abnormally high arterial stiffness compared with other phenotypes.Increasing evidence indicates the deleterious effect of stiffer arteries 1 .In several studies, arterial stiffness was shown more accurate predictor of cardiovascular events than conventional risk scores 13,14 .Meta-analysis showed an increase of 1 m/s in baPWV was associated with a 12% increase in total cardiovascular events, a 13% increase in cardiovascular mortality, and a 6% increase in all-cause mortality 13 .In patients with stable angina, arterial stiffness was associated with all-cause mortality in addition to traditional risk factors 14 .Similarly, in patients with acute ischemic stroke, arterial stiffness was associated with short-term outcomes such as worsening of neurological symptoms and a slower early recovery 15,16 .Arterial stiffness was also linked to worse long-term outcomes in terms of all-cause and vascular mortality after acute ischemic stroke 17 .Additionally, we found that EVA patients had a higher prevalence of hypertension, diabetes, and atrial fibrillation compared to NVA patients, which is consistent with previous research of arterial stiffness 9,18 .Therefore, increased arterial stiffness may be a contributing factor to the correlation between EVA and adverse outcomes in patients with acute ischemic stroke.
In our study, the deteriorating effect of EVA on stroke outcome was more obvious in certain subgroups.In patients with diabetes, EVA showed a higher prognostic value of poor functional outcome than in subjects without.This result was supported by previous studies that showed diabetes accelerates vascular aging and impairs functional recovery after stroke 19,20 .Patients with diabetes also tended to have more risk factors such as hypertension and dyslipidemia (Supplementary Table 1).Moreover, EVA had a greater effect on all-cause mortality in patients with atrial fibrillation than in subjects without.The supplemental finding showed patients with atrial fibrillation had higher CHA 2 DS 2 -VASc scores, were older, and had a history of previous stroke (Supplementary Table 2).Therefore, the burden of these risk factors may have influenced the results 21 .However, the prominent effect of EVA was not consistent across both outcomes.Further studies are needed to elucidate the interplay between diabetes, atrial fibrillation, and vascular aging.
In the current study, EVA was associated with poor functional outcome and mortality, albeit in small numbers.Previous studies included relatively large numbers of EVA subjects, but these were community-based and general population studies 4,5,9 .The researchers also used the extreme distributions of upper and lower 10% to define EVA and SUPERNOVA, respectively 4,5 .This definition could create a gray zone where some NVA subjects are included with EVA and SUPERNOVA subjects 1 .In addition, only EVA was addressed in stroke studies and correlations with cardiovascular risk factors in young or low-risk stroke subtypes were reported 22,23 .However, the present study used an upper and lower bound of 2.5% for vascular aging phenotyping and included acute ischemic stroke patients, which is a strength of the study.SUPERNOVA implies extremely low arterial stiffness for chronological age; however, in this study, SUPERNOVA was not found to be superior to NVA in terms of prognosis.A potential explanation is the higher prevalence of atrial fibrillation and other cardioembolism in SUPERNOVA patients (Table 1), which may mitigate the positive prognostic effect.
This study had several limitations.First, relatively mild stroke patients were included because baPWV measurements require patient cooperation.Second, instead of the gold standard carotid-femoral PWV, baPWV was used for vascular aging phenotyping.However, a strong correlation between the two PWV modalities was reported in previous research 24 .Third, the study was structured as an observational and retrospective analysis, but patients were sequentially enrolled and underwent the same clinical treatment protocol.Fourth, baPWV is related to vascular aging but not identical to it.Therefore, our results show a possible link between vascular aging phenotypes and stroke prognosis.

Conclusion
In the present study, the EVA phenotype was an independent prognostic factor predicting short-term poor functional outcomes and long-term all-cause mortality in acute ischemic stroke patients undergoing baPWV.This finding indicates the vascular aging phenotype, particularly EVA, could help identify high-risk patients among those with relatively mild stroke.

Study population
Patients diagnosed with acute ischemic stroke within 7 days of onset from January 2012 to December 2018 were consecutively enrolled.Every patient underwent neuroimaging with either magnetic resonance imaging (MRI) and/or computed tomography (CT).The condition of the cerebral vessels was assessed using cerebral angiography with MR angiography, CT angiography, or digital subtraction angiography.Systemic evaluations included chest radiography, 12-lead electrocardiography, routine blood tests, and lipid profiling.Transthoracic echocardiography, transesophageal echocardiography, or cardiac CT were performed for selected patients.As part of the standard evaluation, baPWV was measured in all patients, except for subjects with decreased consciousness, impending brain herniation, poor systemic conditions, or lack of informed consent.The median interval between stroke onset and baPWV measurement was 4 days (interquartile range, 2-5 days).The stroke subtype was determined using the Trial of ORG 10172 in Acute Stroke Treatment classification 25 .Patients were appropriately managed and treated according to the guidelines for acute ischemic stroke 26 .

Assessment and vascular aging phenotype
Vascular aging was assessed using baPWV (VP-1000 Plus; Colin Co., Ltd., Komaki, Japan), which is the distance between the brachial and the ankle divided by the delay time between the initial point of the brachial pulse wave and the ankle pulse wave.Vascular aging phenotype was taken from a previous study that used the age quintilespecific 2.5th and 97.5th percentile of baPWV as cutoffs for defining SUPERNOVA and EVA, respectively 9 .Briefly, a baPWV value below the age quintile-specific 2.5th percentile was defined as SUPERNOVA, a baPWV value above the age quintile-specific 97.5th percentile as EVA, and the remaining patients were considered NVA (Supplementary Fig. 2).

Follow-up and outcomes
Patients were followed in the outpatient clinic or with a structured telephone interview at 3 months and annually after discharge.Poor functional outcome was defined as the modified Rankin Scale score ≥ 3 at 3 months.MACE was defined as any development of stroke recurrence, acute coronary syndrome, or all-cause mortality.Stroke recurrence refers to newly developed neurologic symptoms relevant to lesions on brain imaging.The censoring date was December 31, 2019.If a patient's final visit occurred prior to this date, that last visit's date was used as the censoring date.The Institutional Review Board of the Severance Hospital of the Yonsei University Health System approved this study, and due to the retrospective nature of the study, the need for informed consent was waived (approval number: 4-2023-0974).This study was conducted ethically in accordance with the World Medical Association Declaration of Helsinki.

Statistical analysis
Categorical variables are presented as counts with percentages.Continuous variables are presented as either the mean with standard deviation or the median with interquartile range.The significant intergroup difference was assessed using the chi-square and Fisher's exact tests for categorical variables or the one-way analysis of variance and the Kruskal-Wallis tests for continuous variables.Logistic regression analysis was performed to observe the significant factors for poor functional outcome.Survival curves were plotted using the Kaplan-Meier analysis and compared with the log-rank test.Cox proportional hazards regression analysis was performed to determine the significant factors associated with long-term outcomes.To identify the independent association of vascular aging with outcomes, multivariable analysis was utilized with adjustment for covariates such as age, sex, body mass index, NIHSS score at admission, and variables that were significant (p < 0.05) in univariable analysis.For the covariate stroke subtype, small vessel occlusion was used as a reference because it had a better prognosis compared to the other subtypes (Supplementary Table 4).The independent association between vascular aging and long-term outcomes was further confirmed by adjusting for the ASCVD risk factors such as age, sex, hypertension, diabetes, current smoking, total cholesterol, and high-density lipoprotein cholesterol.Subgroup analysis was performed using multivariable logistic or Cox regression analyses based on patient characteristics.All statistical analyses were conducted with SPSS 26 (Chicago, IL, USA) and two-tailed p < 0.05 was considered statistically significant.

Figure1.
Figure1.Distribution of stroke subtypes based on vascular aging.EVA early vascular aging, NVA normal vascular aging, SUPERNOVA supernormal vascular aging.P value was obtained by the Chi-square test.

Figure 2 .
Figure 2. Kaplan-Meier plots according to vascular aging phenotypes.Survival curves for MACE (A), stroke recurrence (B), and all-cause mortality (C).EVA early vascular aging, MACE major adverse cardiovascular event, NVA normal vascular aging, SUPERNOVA supernormal vascular aging.

Figure 3 .
Figure 3. Subgroup analysis based on patient characteristics.Multivariable logistic regression and multivariable Cox regression were utilized for functional outcome (A) and mortality (B), respectively.CE cardioembolism, CI confidence interval, EVA early vascular aging, HR hazard ratio, LAA large artery atherosclerosis, NIHSS National Institutes of Health Stroke Scale, OR odds ratio, small vessel occlusion, UN negative evaluation, UT two or more causes.

Table 1 .
Patient demographic and clinical characteristics.EVA early vascular ageing, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol, NIHSS National Institutes of Health Stroke Scale, NVA normal vascular ageing, SUPERNOVA supernormal vascular ageing.a p-values obtained by comparing groups with and without a given stroke subtype.

Table 2 .
Logistic regression analysis of poor functional outcome at 3 months.Poor functional outcome is defined as the modified Rankin Scale score ≥ 3 at 3 months.
CE cardioembolism, CI confidence interval, EVA early vascular ageing, HDL-C high-density lipoprotein cholesterol, LAA large artery atherosclerosis, LDL-C low-density lipoprotein cholesterol, NIHSS National Institutes of Health Stroke Scale, NVA normal vascular ageing, OR odds ratio, SUPERNOVA supernormal vascular ageing, SVO small vessel occlusion.a Adjusted for age, sex, body mass index, NIHSS score at admission, hypertension, diabetes, current smoking, atrial fibrillation, coronary artery disease, previous stroke, triglyceride, and stroke subtypes.

Table 3 .
Multivariable Cox regression analysis of long-term outcomes.CI confidence interval, EVA early vascular ageing, HR hazard ratio, MACE major adverse cardiovascular event, NIHSS National Institutes of Health Stroke Scale, NVA normal vascular ageing, SUPERNOVA supernormal vascular ageing.Model 1: adjusted for age, sex, body mass index, NIHSS at admission, and variables with p < 0.05 in univariable analysis.Model 2: adjusted for the atherosclerotic cardiovascular disease risk factors (age, sex, hypertension, diabetes, current smoking, total cholesterol, and high-density lipoprotein cholesterol).